Qrvey is an all-in-one, self-service data platform that combines analytics, data collection, and automation technologies.
Qrvey consists of 4 main components which are built on a native cloud architecture to maximize flexibility, scalability and performance. These components are powered by many individual features that can be combined to perform different analysis, automation, or collection related tasks. All of Qrvey components can be deployed as a stand-alone application or be embedded into other applications and platforms through the use of Widgets and APIs.
Qrvey Platform Components
The Admin Portal is an application to manage and monitor your Qrvey instance, Data Router settings, Amazon AWS infrastructure options and application deployments. The app is divided into four sections, Platform, Data Router, Deployments and Data.
In the Platform section you will be able to manage access to your Qrvey instance by creating user accounts, customizing the look and feel of Qrvey to match your own branding and configuring and connecting to third-party services. You will also be able to manage all of the sections and features available to your users.
In the Data Router section you will find the Health Dashboard where you can monitor the health and performance of Data Router. Here you’ll find information and indications for the health of the data service, metadata and Elasticsearch instances. You will also be able to make adjustments to infrastructure such as specify the size and number of servers you’d like to use for both Qrvey and Elasticsearch as well as the amount of concurrency you’d like to use for Lambda functions.
In the Data section, Admins will be able to establish connections to external databases.These connections are used to load data into Qrvey’s Elasticsearch indexes which can be accessed by report designers to create datasets for analytics. The Data Sync feature allows Admins to sync databases with Qrvey’s backend in near real-time or on a scheduled basis.
The Deployments section is used by Admins to deploy Qrvey application content to one or more destinations. It consists of 2 parts, server management and deployment definitions. Servers are added as destinations for new or recurring deployments. Admins can create a release by selecting content from specific user accounts and applications as a deployment package which includes all or some of the components created inside an application.
Data Router is Qrvey’s data integration tool that can collect, augment and transform your data, while making it available to everyone who needs it, wherever they need it. All of these functions are performed in a no-code environment. Qrvey’s Data Router will turn your data into a high-performance data powerhouse that can be leveraged by Qrvey’s analytic and automation platform. With Data Router you can easily push data from anywhere into Qrvey’s Elasticsearch backend and allows you to work with structured, semi- and unstructured data. It also supports a high-volume batch loading and has the power to process high-velocity real-time data.
Data router provides flexible metadata including column mapping, transformations and filters. You can map any structure of data, any types of fields or choose from our growing list of data transformations and functions. Some of these are robust AI and ML transformations such as video and image recognition and advanced text and document analysis capabilities.
It also includes a full suite of administrator tools for testing, debugging and logging, as well as performance and load monitoring for the health of your deployments.
Qrvey Analytics Applications
Qrvey’s business analytics application is built on a modern cloud architecture to maximize flexibility, scalability and performance. It bundles data collection, analytics and automation.
Data Collection technologies enable self-service tools for gathering all types of data through the creation of online forms, surveys and quizzes. It can also integrate with structured, semi-structured and or/unstructured data.
This data can be used in analytic to summarize data with profiles, tabular views, trend analysis or explore text analytics using sentiment and keyword analysis. Users can easily create custom visualizations such as pie, line, heatmap charts as well as combo-charts that include multiple layers, reference lines and more. Interactive analytics support complex filters, drill-down reports and configurable dashboards that can be made available to end users.
In Automation users have the ability to automate actions and trigger alerts based on data values or collected responses. Users can set Workflow triggers that are scheduled, data-driven or initiated from web hooks. The automation engine is a fully self-service, end-user focused interface that is both robust and easy to use.
These 3 technologies bring self-service form and no-code application building to your entire enterprise with an easy-to-use app builder that can be used stand-alone or coupled with your Data Powerhouse.
Qrvey provides a comprehensive REST API that can be accessed via standard HTTP requests and responses (GET, POST, etc.). Developers may use a variety of programming languages and platforms, as most have built-in libraries for HTTP communication. You may use the Qrvey API in order to programmatically work with any of the core Qrvey application features for data collection, automation and analytics or when integrating Qrvey into your own applications.
Setup and Deployments
Qrvey is a 100% Cloud native product built with dozens of AWS services like Elastic Container Service (ECS), DynamoDB, S3, Load Balancers, Auto scaling, SES, SQS, etc. We deploy directly into your own Amazon Web Services (AWS) account. This gives you full control over your installation and data. You can decide how big of a deployment you need and have full control to scale up or down as needed to balance cost with performance.
Qrvey Platform is deployed using a combination of Cloudformation templates and Code Pipelines. This makes the deployment fully automated and there is no downtime during upgrades. An upgrade is as simple as copying a few Zip files into an S3 bucket which will trigger the pipelines and deploy the new version including any updates to the infrastructure.
In this section, we’ll discuss the Qrvey architecture and how all of our components work together to deliver on the promise of a unified, all-in-one data solution.
Working with Qrvey
There are three main ways to interact with Qrvey. First, we offer a robust API that allows for direct interaction with all of Qrvey’s functions for data collection, analytics, automation and information distribution. Second, we offer a suite of pre-built widgets to simplify the process of embedding Qrvey into existing web pages and applications. Every part of the Qrvey platform can easily be embedded.
Finally, there is the Qrvey itself, which is a web-based application where end-users can build forms, analytics, workflows and more. The Qrvey application has been 100% widgetized, ensuring that everything you can do with the app can also be done with embedded widgets.
Qrvey is built on a fully scalable, Cloud architecture utilizing a variety of AWS services to deliver maximum performance for all of your data and application requirements.
On the backend, we leverage Elasticsearch and DynamoDB to support both massive scale and unstructured to semi-structured data.
For developers, we provide a comprehensive set of APIs and widgets to integrate with your existing applications, data and services.
Out of the box, we also provide a number of supporting services to provide advanced analytics, messaging, and additional customizations.
Data Router Architecture
Qrvey DataRouter is built on a system of highly scalable APIs and services that support loading all of your data into Qrvey’s Elasticsearch backend.
The API Gateway routes your data through our metadata and data services for managing everything from large volume historical batch loading, and more real-time live data updates.